Though too many clearly still suffer too much, a large proportion of people live free from fear of starvation or lack of shelter
The US has deindustralized, meaning hard physical labor is not the reality for a lot of people. For a lot of people labor is emotional or symbolic (“knowledge work”)
In other words, for lots of people the economic promise has been fulfilled
It is not coincidental that “Gas Town”’s announcement post mentioned Towers of Hanoi, an undergraduate CS student homework problem that for most students requires thinking hard. It’s designed to encourage a kind of “eureka” moment where recursion as a computer programming technique becomes more clear. GT claims to fulfill the promise of not having to think hard like this anymore: the LLMs will do that thinking for you
It is not coincidental that Gas Town is described as being very expensive. Economic power in the form of asset accumulation is what earns you freedom in this way of conceiving things. If you want the freedom from having to think hard, you’d better accumulate assets
Since the promise is greater collective freedom, endeavoring to accumulate assets is, in this view, a collective good
This differs from effective altruism and other “do good by doing well” conceptions. Rather, the very mechanism of economics produces collective wealth, so the story goes, which means the more active one is as an economic agent, the more collective good one produces (“wealth” and “good” being conflated)
Accumulation of assets is the scorecard, so to speak, of such enhanced economic activity, and the individual reward can then be freedom from having to think hard
Lotka’s maximum power principle (supposedly) dictates that those entities that transform the most power into useful organization are most fit from an evolutionary standpoint
Ernst Juenger’s notion of “total mobilization” brings this principle to politics/political economy/geopolitics: those nations that “totally” mobilize their national resources are the ones that will dominate geopolitically
See, for instance, the RAND Corporation’s Commission on the National Defense Strategy: “The Commission finds that the U.S. military lacks both the capabilities and the capacity required to be confident it can deter and prevail in combat. It needs to do a better job of incorporating new technology at scale; field more and higher-capability platforms, software, and munitions; and deploy innovative operational concepts to employ them together better.” (emphasis mine). In summary: the US is about to be outcompeted (lacks fitness); in response, it should go big (“at scale”, “more”) in an organized way (“deploy innovative operational concepts”, “employ them together better”)
The rhetoric around LLM-based AI includes similar language, exemplified in the GT post: burn through as much infrastructural resources as possible to produce organized outputs “at scale”, while avoiding having human beings think too hard to produce those outputs, an indication that the power was burned to produce useful organization
LLM-based AI plays a prominent role in US federal government strategy, particularly military strategy, with language about dominance serving to justify its use
It is not coincidental that Gas Town uses many orders of magnitude more resources to solve the Towers of Hanoi problem (“Burn All The Gas” Town). This rhetoric dovetails perfectly with the “total mobilization” concept
In the future I see that Gen AI models will have a Fair Trade certificate like coffee and chocolate have, or a sustainable certificate like tuna and other fish have.
"One notable MIT study found that 95 percent of companies that integrated AI saw zero meaningful growth in revenue. For coding tasks, one of AI’s most widely hyped applications, another study showed that programmers who used AI coding tools actually became slower at their jobs.”
A lot of generative AI stuff isn’t really working,” Gownder told The Register. “And I’m not just talking about your consumer experience, which has its own gaps, but the MIT study that suggested that 95 percent of all generative AI projects are not yielding a tangible [profit and loss] benefit. So no actual [return on investment.]”
https://futurism.com/artificial-intelligence/ai-failing-boost-productivity
Learning a new AI-related term: workslop.
"The insidious effect of workslop is that it shifts the burden of the work downstream, requiring the receiver to interpret, correct, or redo the work. In other words, it transfers the effort from creator to receiver."
https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity
#workslop #AI #slop #GenAI #technology #news #TechNews #study
Finally, after an epic battle against Gitea CI:
The definitive answer to the question, "Is AI intelligent yet?"
https://github.com/searxng/searxng/issues/2163
https://github.com/searxng/searxng/issues/2008
https://github.com/searxng/searxng/issues/2273
Folks, I need to talk about this Grok/X/ #AI thing. I will not give details. But the vile aspects of these news, added to the downfall of mainstream journalism quoting Grok as if it was a real entity... I think all of this should give people pause. Like, where are we fucking going. It's been several years now and we have not seen any glimpse of a bright future with this #GenAI shitshow. Consider this an exercise of screaming into the void 🧵
I wanted to share my opinions on #AI, specifically #genAI. Thanks for reading!
https://medium.com/@santiagorhenals/my-opinions-on-ai-us-00d3b4168e87
RE: https://tldr.nettime.org/@tante/116917227123480616
It is interesting that they are trying to establish a new term "transformative AI" (probably because #genAI is burned as a term that just signifies slop)
Ist generative »KI« die neue Zwangsreligion, eine kollektive Wahnvorstellung oder das trojanische Pferd des aufziehenden Technofaschismus? Oder alles zugleich?
Solche Fragen gehen mir durch den Kopf, seit ich den Vortrag »Zauberhafte KI-Welt« von @Katika online sah.
Am kommenden Donnerstag ist Katika Kühnreich in Bielefeld, wo sie ab 19:30 Uhr eine aktualisierte Fassung dieses Vortrags halten wird. Wir @Datenpunks haben sie eingeladen und laden euch ein, dazuzukommen:
Wann? Do., 21.05.2026
Wo? Buchladen Eulenspiegel, Hagenbruchstraße 7, 33602 Bielefeld
Wer einen Sitzplatz will, sollte sich anmelden (gern pseudonym): https://datenpunks.de/event/zauberhafte-ki-welt-energie-und-arbeit-der-ki-und-was-sie-mit-gesellschaften-macht/
#kiKritik #KatikaKühnreich #Bielefeld #OWL #Ostwestfalen #Veranstaltung #Vortrag #genai #antifa #Technofaschismus
"There have been several incidents where interaction with a chatbot has been cited as a direct or contributing factor in a person's suicide or other fatal outcome. In some cases, legal action was taken against the companies that developed the AI involved."
CW: Death, of course.
"Turning to generative AI for your filmmaking, even to make a point about its own uselessness, is to accept defeat."
https://www.avclub.com/deepfaking-sam-altman-lets-ai-direct-the-movie-which-is-accepting-defeat
Our source said that the goal of the project is to make people aware of AI's Achilles' Heel – the ease with which models can be poisoned – and to encourage people to construct information weapons of their own.
I wish we had more people writing more sophisticated concerns about the harms of AI.
"Slop" criticism is important because I think many of us feel we are being gaslit into believing that generative AI is currently creating quality creative output, while Al (henceforth Alfred) is overwhelmingly creating mediocre quality creative work.
Every past winter, Alfred survives in a more focused and refined form. Eliza was a toy chatbot of the 1960s, but what emerged from that is expanded investment in things like Natural Language Processing and Markov chains.
Markov chains have always been powerful, but through computing applications, Markov chains led to advancing capabilities in weather prediction, financial modeling, and eventually Google PageRank and bioinformatics/biostatistics (BLOSUM/BLAST for analyzing/predicting/correlating amino acid chain similarities).
The next boom and winter led Alfred to popularize classic machine learning into practical applications in consumer products: recommendation engines and clustering algorithms that formed the core of products from the Netflix prize to Spotify, Pandora, Amazon, and eventually virtually every consumer retailer has multiple machine learning products supporting everything from suggested products to search results to their own logistics and sales and financial modeling.
Learn from the past. Prepare for the future. Al will learn how to spell strawberry, write basic documents and code more effectively, and make fewer basic mistakes. Think beyond that. What are the emerging harms that come AFTER all of that?
#AI #GenAI #GenerativeAI #generative_ai_risks #generative_ai_concerns
In which I build Unicode character tables and fail to serialize large automata, “Losing 1½ Million Lines of Go“:
https://www.tbray.org/ongoing/When/202x/2026/01/14/Unicode-Properties
(And in which I find myself sliding into the #GenAI-is-ok-for-coding camp.)
